Protecting content on a display device from a field-of-view of a person or device

ABSTRACT

A server can receive data about attributes of user devices that includes sensors for capturing information about environments in which the user devices are located. The server can determine various risk profiles using the attributes. The risk profiles can indicate likelihoods of content on the user devices being viewed by persons other than users of the user device. The server can also transmit data indicating a risk profile of the various risk profiles to a user device. The user device can use the risk profile received from the server to identify confidential content displayed on the user device and protect the confidential content.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of and claims priority from U.S.patent application Ser. No. 15/487,129, filed Apr. 13, 2017, the entiredisclosure of which is incorporated herein by reference.

TECHNICAL FILED

The present disclosure relates generally to user interface devices. Morespecifically, but not by way of limitation, this disclosure relates toprotecting content displayed on a user interface device from afield-of-view of a person or other device.

BACKGROUND

Many devices include a display device that can be used to providecontent to a user of the device. The content can include text, images,sounds, videos, etc. A spectator (e.g., another person near the deviceor looking at the device) may also view content provided on the displaydevice. Another device near the device may also capture or view contenton the display device. But, in some instances, the content provided onthe display device may not be intended to be viewed by the spectator orthe other device, but may nonetheless be exposed to view by thespectator or other device.

SUMMARY

In one example, a server of the present disclosure includes a processingdevice and a communication device for transmitting or receiving data viaa network. The server also includes a non-transitory computer-readablemedium communicatively coupled to the processing device. The processingdevice is configured to: receive data about attributes from user deviceswith sensors for capturing information about environments in which theuser devices are located; and determine a plurality of risk profilesusing the attributes. The plurality of risk profiles can indicatelikelihoods of content on the user devices being viewed by persons otherthan users of the user devices. The processing device is also configuredto transmit, to a first user device and using the communication device,data indicating a risk profile of the plurality of risk profiles. Therisk profile can be used by the first user device for identifyingconfidential content displayed on the first user device and protectingthe confidential content.

In another example, a user device of the present disclosure includes adisplay device and a communication device for transmitting or receivingdata via a network. The user device also includes a sensor deviceconfigured for capturing information about a field of view of athird-party device or a person other than a user of the user device anda processing device. The user device further includes a non-transitorycomputer-readable medium communicatively coupled to the processingdevice. The non-transitory computer-readable medium comprisesinstructions that are executable by the processing device for:displaying, via the display device, content comprising public contentand confidential content; receiving data from a server through thecommunication device; receiving, from the sensor device, capturedinformation about the field of view of the third-party device or theperson other than the user of the user device; identifying theconfidential content displayed via the display device; using the datareceived from the server and the captured information to determine toprotect the confidential content; and in response to determining toprotect the confidential content, protecting the confidential contentfrom view by the third-party device or the person other than the user ofthe user device.

In another example, a method of the present disclosure includes:receiving, by a processor of a server, data indicating a first attributeof a first user device; and training, by the processor, amachine-learning algorithm to determine a various risk profilesassociated with various attributes using the first attribute of thefirst user device. A risk profile can indicate a likelihood of contenton the first user device being viewed by a person other than a user ofthe user device. The method further includes: determining, by theprocessor and using the machine-learning algorithm, a first risk profileassociated with the first attribute of the first user device; andtransmitting, by the processor and to the first user device, dataindicating the first risk profile. The first user device can use thefirst risk profile to identify confidential content displayed on thefirst user device and protect the confidential content.

The details of one or more aspects and examples are set forth in theaccompanying drawings and the description below. Other features andaspects will become apparent from the description, the drawings, and theclaims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-B are block diagrams of an example of an environment in which auser device for protecting content based on a detected field-of-view canoperate according to some aspects.

FIG. 2 is a flow chart depicting an example of a process for protectingcontent based on a detected field-of-view of a person according to someaspects.

FIG. 3 is an example of a series of user interfaces that can begenerated by the user device for protecting content based on a detectedfield-of-view according to some aspects.

FIG. 4 is a flow chart depicting another example of a process forprotecting content from a field-of-view of a person or other deviceaccording to some aspects.

FIG. 5 is a flow chart depicting an example of a process for protectingcontent based on a detected field-of-view of a device according to someaspects.

DETAILED DESCRIPTION

Certain aspects and features of the present disclosure relate toprotecting content displayed on a user interface device based on adetected field-of-view of a person or another device. Protecting contentcan include, for example, preventing content displayed on a display of acomputing device from being viewed by a person other than a user of thecomputing device or by another device.

In one example, a computing device, such as a smartphone or a tablet,includes a sensor and a display. The display can display or outputvarious content (e.g., text, images, sounds, videos, animations, virtualobjects, virtual animations, etc.). The sensor can detect afield-of-view or a direction of an eye gaze of a person, other than theuser of the computing device, relative to the display. The sensor canthen transmit a signal to a processor indicating the detectedfield-of-view of the other person and the processor determines whetherthe detected field-of-view of the other person is directed at or towardcontent displayed on the display. The processor can determine oridentify confidential or sensitive content on the display (e.g., contenton the display that is not intended to be viewed by a person other thanthe user of the computing device) and determine whether the confidentialor sensitive content is within the field-of-view of the other person.The processor can control the display content and cause the confidentialor sensitive content to change so that it is not viewable on thedisplay. As an example, the processor transmits a signal to the displayto cause the display to hide or blur the confidential content from view.

The sensor can also detect that the field-of-view or direction of theeye gaze of the other person is no longer directed at or toward thedisplay of the computing device and, in response, transmits a signal tothe processor indicating that the field-of-view or direction of the eyegaze of the other person is no longer directed at or toward the display.The processor can then transmit a signal to the display to reveal orunprotect the confidential content. As an example, the processor causesthe display to unhide or not blur the confidential or sensitive contentsuch that the user of the computing device can view the confidential orsensitive content.

The computing device can also or alternatively protect the confidentialcontent based on a detected field-of-view of another device (e.g., acamera) near the computing device in substantially the same manner asdescribed above. For example, the computing device determines that acamera is directed at or toward the display and can protect confidentialcontent displayed on the display.

In some examples, the computing device determines an amount of theconfidential content to hide or protect or a duration of time to hidethe confidential content based on a detected field-of-view of the otherperson or the other device.

A server may be communicatively coupled to the computing device toreceive data when the processor determines that the field-of-view or eyegaze of the other person is directed at or toward content on thedisplay. For example, the processor transmits a location of thecomputing device, a type of the computing device, an application orprogram being executed by the processor, a type of network connectionassociated with the computing device, or any other data about thecomputing device when the field-of-view or eye gaze of the other personis directed at or toward content on the display. The server candetermine a risk profile associated with a particular location, aparticular type of computing device, a particular application orprogram, a particular type of network, etc. A risk profile can indicatea likelihood of content on the display being exposed to view by a personother than the user of the computing device. For example, the serverdetermines a risk profile for a particular location that indicates thatthere is a high risk or likelihood that content on a display of acomputing device at that location will be exposed to view by a personother than the user of the computing device. In some examples, theserver determines the various risk profiles by training amachine-learning algorithm to determine the risk profiles.

The server can use the analysis to change the relative risk threshold bywhich other computing devices communicatively coupled to the serverprotect confidential or sensitive information. For example, the serverobtains data from the other computing device indicating a location ofthe other computing device and transmits a signal to the processor ofthe other computing device to instruct the other computing device toprotect confidential information even if that device has not detected afield-of-view of another person or camera. In some examples, theprocessor of the other computing device determines an amount of theconfidential content to hide or protect based on a received risk profilefrom the server. In another example, the processor of the othercomputing device determines a duration of time to hide the confidentialcontent based on the received risk profile. As an example, the processorof the other computing device receives a signal from the serverindicating that a location of the other computing device is associatedwith a high risk-profile. In this example, the processor of the othercomputing device can hide a majority of the confidential contentdisplayed on the other computing device.

In another example, a computing device can receive user input indicatinga particular risk profile. If the computing device receives a low riskas a profile, such as if the user is at home, the computing device mayonly protect highly confidential information or only protectconfidential information for a short amount of time from being viewed bya detected field-of-view of a non-user person or another device. If thecomputing device receives a high risk as a profile, such as if the useris at a highly populated area (e.g., an airport), the computing devicemay protect all or substantially all of the confidential information orprotect the confidential information for an extended amount of time frombeing viewed by a field-of-view of a non-user person or another device.

In this manner, a computing device can protect certain confidential orsensitive content displayed on a display of the computing device fromview by a person other than the user of the computing device based onthe field-of-view of the other person.

These illustrative examples are given to introduce the reader to thegeneral subject matter discussed here and are not intended to limit thescope of the disclosed concepts. The following sections describe variousadditional features and examples with reference to the drawings in whichlike numerals indicate like elements, and directional descriptions areused to describe the illustrative examples but, like the illustrativeexamples, should not be used to limit the present disclosure.

FIGS. 1A-B is a block diagram of an example of an environment 100 inwhich a user device 102 a-c for protecting content based on a detectedfield-of-view can operate. The environment 100 includes user devices 102a-c and a server 104. Each user device 102 a-c can communicate withanother device (e.g., the server 104) via a network 110 or receive anindicia of user input (e.g., if a user programs the user device 102 a-cto include data). The server 104 can transmit data to, or receive datafrom, any device in the environment 100 (e.g., the user devices 102 a-c)or any other device. The server 104 can store data received or obtainedin a database 106. In this example, the environment 100 also includesthe network 110, which can be any network that facilitates communicationof data by the user devices 102 a-c, the server 104, or any other devicein the environment 100.

Each user device 102 a-c can be, for example, a mobile device, asmartphone, a laptop, tablet, e-reader, smartwatch, etc. In someexamples, each user device 102 a-c includes one or more components forprotecting content based on a detected field-of-view. For example, theuser device 102 a includes a processor 112 a, a bus 114 a, a database115 a, and a memory 116 a. The processor 112 a can execute one or moreinstructions for operating the user device 102 a. For example, theprocessor 112 a executes instructions 118 a stored in the memory 116 ato perform the operations. Non-limiting examples of the processor 112 ainclude a Field-Programmable Gate Array (“FPGA”), anapplication-specific integrated circuit (“ASIC”), a microprocessor, etc.

The processor 112 a can be communicatively coupled to the memory 116 avia the bus 114 a. The memory 116 a may include any type of memorydevice that retains stored information when powered off. Non-limitingexamples of the memory 116 a include electrically erasable andprogrammable read-only memory (“EEPROM”), flash memory, or any othertype of non-volatile memory. In some examples, at least some of thememory 116 a includes a computer-readable medium from which theprocessor 112 a can read instructions 118 a. The computer-readablemedium can include electronic, optical, magnetic, or other storagedevices capable of providing the processor 112 a with computer-readableinstructions or other program code. Non-limiting examples of a computerreadable-medium include (but are not limited to) magnetic disks, memorychips, ROM, random-access memory (“RAM”), an ASIC, a configuredprocessor, optical storage, or any other medium from which a computerprocessor can read instructions. The instructions 118 a can includeprocessor-specific instructions generated by a compiler or aninterpreter from code written in any suitable computer-programminglanguage, including, for example, C, C++, C#, etc.

The user device 102 a can include input/output interface components(e.g., a display device 120 a and a communication device 122 a). Theuser device 102 a can also include other input/output interfacecomponents such as, for example, a keyboard, a touch-sensitive surface,a mouse, and additional storage. In some examples, the user device 102 aincludes input/output interface components that may be used tofacilitate wired or wireless connection to devices such as one or moredisplay devices 120 a, game controllers, keyboards, mice, joysticks,cameras, buttons, speakers, microphones and/or other hardware used toinput or output data.

The user device 102 a can transmit or receive data via the communicationdevice 122 a. The communication device 122 a can represent one or morecomponents that facilitate a network connection. In some examples, thecommunication device 122 a is wireless and includes wireless interfacessuch as IEEE 802.11, Bluetooth, or radio interfaces for accessingcellular telephone networks (e.g., transceiver/antenna for accessing aCDMA, GSM, UMTS, or other mobile communications network). In anotherexample, the communication device 122 a is wired and includes interfacessuch as Ethernet, USB, IEEE 1394, or a fiber optic interface. The userdevice 102 a can transmit or receive data (e.g., transmit data on atelecommunication network or transmit data to the server 104, thedatabase 106, or another device in the environment 100) via thecommunication device 122 a. In another example, the user device 102 atransmits data to a remote location (e.g., to another computing deviceoutside the environment 100 or a remotely located server or device) viathe communication device 122 a. In the example depicted in FIG. 1, theuser device 102 a transmits and receives data via a wireless interface.In other examples, the user device 102 a transmits and receives data viaa wired interface.

The user device 102 a can include one or more sensors 124 a that cancapture information about an environment in which the user device 102 ais located. The sensor 124 a can include, for example, a globalpositioning system (GPS) unit, a range sensor, a Bluetooth device, acamera, an infrared sensor, a quick response (QR) code sensor, etc. Insome examples, the sensor 124 a is any device for detecting an eye gaze,line-of-sight, or field-of-view of a person (e.g., a person other than auser of the user device 102 a). As an example, the sensor 124 a includesa camera or is incorporated into the camera. The sensor 124 a can detecta direction of the person's field-of-view with respect to content (e.g.,texts images, sounds, videos, characters, virtual objects, virtualanimations, etc.) displayed on display device 120 a. For example, thesensor 124 a captures an image of an eye of a person other than the userof the user device 102 a. The sensor 124 a can then transmit a signalindicating the captured image to the processor 112 a and the processor112 a can determine the direction of the field-of-view of the personrelative to content on the display device 120 a by using imageprocessing. In another example, the sensor 124 a monitors movements ofan eye of the other person or muscles near the eye of the other personand transmit signals indicating the monitored movements to the processor112 a. The processor 112 a can then determine the direction of theperson's field-of-view relative to content on the display device 120 abased on the monitored movements. In still another example, the sensor124 a monitors or measures electrical activity of muscles moving an eyeof the other person and the processor 112 a can determine the directionof the person's field-of-view relative to content on the display device120 a.

In some examples, the sensor 124 a detects an eye gaze, line-of-sight,or field-of-view of a person other than the user of the user device 102a through various methods and techniques including, for example, byanalyzing the person's body or head posture.

The sensor 124 a can additionally, or alternatively, detect a locationof another device (not shown), a presence of the other device, orproximity of the other device to the user device 102 a via varioustechniques or methods. For example, the sensor 124 a can detect anotherdevice and transmit a signal about the other device to the processor 112a. The processor 112 a can then determine a location of the other deviceor a proximity of the other device to the user device 102 a. In anotherexample, the sensor 124 a is a Bluetooth device or other network devicethat detects a location of another Bluetooth device by analyzing thestrength of a signal between the sensor 124 a and the other Bluetoothdevice or network device. In some examples, the sensor 124 a detects adistance between the sensor 124 a or the user device 102 a and anothercomputing device (e.g., based on the strength of the Bluetooth signalbetween the sensor 124 a and the other computing device).

The sensor 124 a can also detect a location or proximity of anotherdevice that includes a camera or sensor that may view or capture contenton the display device 120 a. The sensor 124 a can then transmit a signalto the processor 112 a and the processor 112 a can determine whether thecamera or sensor of the other device is directed at or toward thedisplay device 120 a. For example, the sensor 124 a captures an image ofthe other device and transmits a signal indicating the captured image tothe processor 112 a and the processor 112 a determines the direction ofthe field-of-view of the camera or sensor of the other device relativeto content on the display device 120 a using various image processingmethods and techniques.

The processor 112 a may be communicatively coupled to a single sensor124 a, and in other examples, processor 112 a may be in communicationwith various sensors 124 a, for example, a camera and a Bluetoothdevice. While in the examples described above, the sensor 124 a can beseparate from the processor 112 a and transmit one or more signals tothe processor 112 a, in some examples, the sensor 124 a can include theprocessor 112 a and the processor 112 a can receive or obtain data fromthe sensor 124 a and analyze the data.

The memory 116 a can include one or more modules for protecting contentbased on a detected field-of-view. For example, the memory 116 aincludes a content provision module 128 a. The content provision module128 a can include one or more instructions stored on a computer-readablestorage medium (e.g., the memory 116 a) and executable by the processor112 a. When executed by the processor 112 a, the computer-executableinstructions can cause the processor 112 a to provide content to a user(e.g., to a user of the user device 102 a or another user) via thedisplay device 120 a. The content provided via the display device 120 acan include public content or confidential content. Public content caninclude, for example, content intended to be viewed by the user of theuser device 102 a that may also be viewed by a person other than theuser of the user device 102 a or by another device (e.g., a time of day,a current date, etc.). Confidential or sensitive content can includecontent provided on the display device 120 a that is not intended to beviewed by any person other than the user of the user device 102 a.Examples of confidential content include, but are not limited to, bankaccount information, identification information, etc.

The memory 116 a also includes a detection module 130 a that can includeinstructions executable by the processor 112 a to cause the processor112 a to determine a direction of an eye gaze or field-of-view of aperson other than a user of the user device 102 a through variousmethods and techniques. In some examples, the detection module 130 adetermines the direction of the eye gaze or field-of-view based onsensor signals received from sensor 124 a. For example, the detectionmodule 130 a is electrically or communicatively coupled to the sensor124 a and receives data from the sensor 124 a indicating an image of aneye of the person, movements of an eye of the person, movements ofmuscles near an eye of the person, electrical activity of muscles movingan eye of a person, the person's body or head posture, or any other datadetected by the sensor 124 a. The detection module 130 a can then causethe processor 112 a to determine a direction of an eye gaze orfield-of-view of the person other than a user of the user device 102 abased on the data received from the sensor 124 a. The detection module130 a can also determine the direction of the eye gaze or field-of-viewof the other person relative to the display device 120 a. As an example,the detection module 130 a receives or obtains data from the sensor 124a and determines whether the other person is looking at or toward thedisplay device 120 a (e.g., looking at or toward content displayed onthe display device 120 a).

The detection module 130 a can additionally, or alternatively, cause theprocessor 112 a to determine a location of another device (not shown) orproximity of the device to the user device 102 a. The detection module130 a can determine the location or proximity of the other device basedon sensor signals received from the sensor 124 a. For example, thedetection module 130 a obtains or receives data about another devicefrom the sensor 124 a and causes the processor 112 a to determine thelocation of the other device or the proximity of the other device to theuser device 102 a based on the data received from the sensor 124 a. Asan example, the sensor 124 a is a Bluetooth device or other networkdevice that detects another Bluetooth device and the detection module130 a causes the processor 112 a to determine a location of the otherBluetooth device by analyzing the strength of a signal between thesensor 124 a and the other Bluetooth device. In another example, thedetection module 130 a causes the processor to determine a location ofanother device or proximity of the device to the user device 102 a viaany suitable technique or method.

In some examples, the detection module 130 a determines a location orproximity of another device that includes a camera or sensor that mayview or capture content on the display device 120 a of the user device102 a. The detection module 130 a can determine the location orproximity of the other device based on sensor signals received orobtained from the sensor 124 a. As an example, the detection module 130a obtains data indicating a presence, position, location, or attributeof the other device from the sensor 124 a and obtains data indicatingwhether the device includes a camera or sensor that may view or capturecontent on the display device 120 a. The detection module 130 a can thencause the processor 112 a to determine whether the camera or sensor ofthe other device is directed at or toward the display device 120 a. Asan example, the sensor 124 a captures an image of the other device andtransmits a signal indicating the captured image to the processor 112 aand the processor 112 a determines the direction of the field-of-view ofa camera or sensor of the other device relative to content on thedisplay device 120 a based on the image by using various imageprocessing methods and techniques.

The memory 116 a also includes a content identification module 132 a,which can be electrically or communicatively coupled to the contentprovision module 128 a. The content identification module 132 a canidentify or determine confidential or public content provided by thecontent provision module 128 a and displayed via the display device 120a. For example, the content provision module 128 a causes the processor112 a to provide content via the display device 120 a. The content caninclude public content (e.g., a current date) and confidential content(e.g., a bank account number associated with the user of the user device102 a). The content identification module 132 a can then identify theconfidential content or the public content being displayed on thedisplay device 120 a.

The memory 116 a also includes a content protection module 134 a thatcan protect content displayed via the display device 120 a. The contentprotection module 134 a can be electrically or communicatively coupledto the content identification module 132 a and can receive or obtaindata indicating that confidential content is being displayed via thedisplay device 120 a. The content protection module 134 a can also beelectrically or communicatively coupled to the detection module and canreceive or obtain data indicating that an eye gaze or field-of-view of aperson other than a user of the user device 102 a is directed at ortoward content on the display device 120 a. The content protectionmodule 134 a can cause the processor 112 a to hide the confidentialcontent from view by the other person to protect the confidentialcontent from the other person. As an example, the processor 112 atransmits a signal to the content provision module 128 a or the displaydevice 120 a to cause the display device 120 a to hide or blur at leasta portion of the confidential content (e.g., hide or blur a portion of abank account number displayed via the display device 120 a).

The content protection module 134 a can also unprotect or reveal contentfor view on the display device 120 a. For example, the contentprotection module 134 a obtains or receives data from the sensor 124 aindicating an image of an eye of the other person, movements of an eyeof the other person, movements of muscles near an eye of the otherperson, electrical activity of muscles moving an eye of the otherperson, the other person's body or head posture, or any other datadetected by the sensor 124 a. The content protection module 134 a canthen determine that the eye gaze or field-of-view of the other person isno longer directed at or toward the display device 120 a (e.g., directedaway from the display device 120 a) based on the obtained or receiveddata. In this example, the content protection module 134 a causes theprocessor 112 a to transmit a signal to the content provision module 128a or the display device 120 a to unhide or reveal the confidentialcontent for view by the user of the user device 102 a (e.g., reveal thepreviously hidden portion of the bank account number displayed on thedisplay device 120 a).

FIG. 3 is an example of a series of user interfaces 300, 302 that can begenerated by the user device 102 a-c for protecting content based on adetected field-of-view according to some aspects. The user device 102 acan generate a first user interface 300 for displaying content on thedisplay device 120 a. For example, the content provision module 128 a ofthe user device 102 a causes the user device 102 a to display the userinterface 300 via the display device 120 a of the user device 102 a. Theuser interface 300 includes public content, such as a current date, andconfidential content, such as an account number, a current accountbalance, and a date of a last account deposit.

The user device 102 a can also generate another user interface 302. Forexample, a content protection module 134 a of the user device 102 a cancause a processor 112 a of the user device 102 a to generate the userinterface 302 to hide confidential content on the display device 120 afrom view to protect the confidential content. For example, theprocessor 112 a transmits a signal to the content provision module 128 aor the display device 120 a to generate the interface 302 and cause theaccount number, current account balance, and the date of a last accountdeposit to be hidden from view.

As described above, the content protection module 134 a can unprotect orreveal content for view on the display device 120 a. For example, thecontent protection module 134 a causes the processor 112 a to transmit asignal to the content provision module 128 a or the display device 120 ato generate and output the user interface 300 to unhide or reveal theconfidential content for view by the user of the user device 102 a. Inthis example, the display device 120 a can unhide the account number,current account balance, and the date of a last account depositpreviously hidden from view in the user interface 302.

Returning to FIG. 1, in some examples, the content protection module 134a receives or obtains data from the content identification module 132 athat indicates that confidential content is being displayed via thedisplay device 120 a. The content protection module 134 a can alsoreceive or obtain data from the detection module 130 a that indicatesthat a direction of a field-of-view of another device is directed at ortoward the display device 120 a and the content protection module 134 acan cause the processor 112 a to hide confidential content from view bythe other device to protect the confidential content. The contentprotection module 134 a can also unprotect or reveal the confidentialcontent in response to determining that the direction of thefield-of-view of the other device is no longer directed at or toward thedisplay device 120 a.

In some examples, the content protection module 134 a determines anamount of the confidential content to hide or a duration of time to hidethe confidential content based on the detected field-of-view of theother person or the other device. As an example, the content protectionmodule 134 a causes the processor 112 a to hide all or substantially allof the confidential content in response to determining that thedirection of the field-of-view of the other person or the other deviceis directed at or toward the display device 120 a. As another example,the content protection module 134 a causes the processor 112 a to hidethe confidential content for a duration of time (e.g., two seconds, fiveseconds, or any suitable duration of time) in response to determiningthat the direction of the field-of-view of the other person or otherdevice is directed at or toward the display device 120 a.

The server 104 can be electrically or communicatively coupled to theuser devices 102 a-c and can receive or obtain data from the userdevices 102 a-c. For example, the server 104 includes a communicationdevice 107 that can be configured in substantially the same manner asthe communication device 122 a-c. The server 104 can also include aprocessor 136, a bus 138, and a memory 140, each of which can beconfigured in substantially the same manner as the processor 112 a-c,the bus 114 a-c, and the memory 116 a-c, although they need not be. Theserver 104 can store data obtained or received from the user devices 102a-c (e.g., via the communication device 107) in the database 106.

The user devices 102 a-c can transmit data about an attribute of theuser devices 102 a-c to the server 104. As an example, the user device102 a transmits data indicating a location of the user device 102 a, atype of the user device 102 a (e.g., a laptop or a smartwatch or a sizeof the user device 102 a), an application or program being executed bythe processor 112 a of the user device 102 a, a type of networkconnection associated with the user device 102 a, or any other dataassociated with the user device 102 a. For example, the user device 102a includes a global positioning system (“GPS”) for providing dataindicating a location of the user device 102 a and the user device 102 atransmits data indicating the location to the server 104. As anotherexample, the user device 102 a is connected to a wireless network andthe user device 102 a transmits data associated with the wirelessnetwork to the server 104. In some examples, the user devices 102 a-ccan transmit data associated with the user devices 102 a-c in responseto determining that an eye gaze or field-of-view of a person other thana user of the user device 102 a-c is directed at or toward content onthe display device 120 a-c.

The memory 140 of the server 104 can include one or more instructionsstored on a computer-readable storage medium (e.g., the memory 140) andexecutable by the processor 136. When executed by the processor 136, thecomputer-executable instructions can cause the processor 136 to performone or more operations. For example, the memory 140 includes amachine-learning algorithm module 108 that receives or obtains dataabout an attribute of the user devices 102 a-c. The machine-learningalgorithm module 108 can then train a machine-learning algorithm basedon the data obtained or received from the user devices 102 a-c. Forexample, the machine-learning algorithm module 108 receives dataindicating a location of the user device, a type of the user device 102a-c, an application or program executed using the user device 102 a-c,or a type of network connection associated with the user device 102 a-cwhen the user device 102 a-c determines that an eye gaze orfield-of-view of a person other than a user of the user device 102 a-cis directed at or toward content on the display device 120 a-c. Themachine-learning algorithm module 108 can then train themachine-learning algorithm based on the data. A machine-learningalgorithm can be a machine-learning model that uses statistical learningalgorithms that are used to estimate or approximate functions thatdepend on a large number of inputs in a non-linear, distributed, andparallel manner. An example of a machine-learning algorithm includes,but is not limited to, a neural network. A computer learningmachine-learning algorithm can include an interconnected group of nodes,called neurons. A machine-learning algorithm can include input nodes,output nodes, and intermediary nodes. In some examples, the connectionsbetween each node are weighted with a set of adaptive weights that aretuned by a learning algorithm, and are capable of approximatingnon-linear functions of their inputs. The machine-learning algorithmmodule 108 can train the machine-learning algorithm to determine a riskprofile associated with an attribute of the user device 102 a-c. Forexample, the machine-learning algorithm module 108 includes a riskprofile module 109 that determines various risk profiles associated withvarious attributes. A risk profile can indicate a likelihood or riskthat content displayed on the user device 102 a-c will be exposed toview by a person other than the user of the user device 102 a-c. Themachine-learning algorithm can use the risk profile module 109 to trainthe machine-learning algorithm to determine various risk profilesassociated with various attributes of the user devices 102 a-c based onthe data obtained or received from the user devices 102 a-c. In someexamples, the server 104 stores the various risk profiles and thevarious attributes of the user devices 102 a-c in the database 106.

For example, the machine-learning algorithm module 108 receives dataindicating a location of the user device 102 a when the user device 102a determines that an eye gaze or field-of-view of a person other than auser of the user device 102 a is directed at or toward content on thedisplay device 120 a. The machine-learning algorithm module 108 can alsoreceive data indicating a location of the user device 102 b when theuser device 102 b determines that an eye gaze or field-of-view of aperson other than a user of the user device 102 b is directed at ortoward content on the display device 120 b. The machine-learningalgorithm module 108 can then use the risk profile module 109 to trainthe machine-learning algorithm to determine a risk profile associatedwith the location of the user device 102 a or the location of the userdevice 102 b. As an example, the risk profile module 109 uses themachine-learning algorithm to compare the location of the user device102 a and the location of the user device 102 b and determine asimilarity or correspondence between the locations based on thecomparison. The risk profile module 109 can then train themachine-learning algorithm to determine a risk profile associated withthe locations of the user devices 102 a-b based on the similarity orcorrespondence. For example, the risk profile module 109 trains themachine-learning algorithm to compare the locations of the user devices102 a-b and determine that the locations are the same or substantiallythe same. The risk profile module 109 can then train themachine-learning algorithm to determine that the locations of the userdevices 102 a-b are associated with a high risk-profile (e.g., thatthere is a high likelihood that content displayed on a computing deviceat that location will be viewed by a person other than the user of thecomputing device) in response to determine that the locations are thesame or substantially the same.

In some examples, the machine-learning algorithm module 108 uses therisk profile module 109 to train the machine-learning algorithm todetermine a risk profile associated with an attribute of a subsequentuser device based on a determined risk profile. As an example, the riskprofile module 109 obtains data indicating a location of the user device102 c and compares the location of the user device 102 c and thelocation of user devices 102 a-b. The risk profile module 109 can thenuse the machine-learning algorithm to determine that the location of theuser device 102 c is the same or substantially the same as the locationof the user device 102 a or 102 b based on the comparison. The riskprofile module 109 can then train the machine-learning algorithm todetermine that the location of the user device 102 c is associated witha high risk-profile. As another example, the risk profile module 109trains the machine-learning algorithm to determine that the location ofthe user device 102 c is associated with a low-risk profile in responseto determining that the location of the user device 102 c is notsubstantially the same as the location of the user device 102 a or 102b.

The server 104 can use the machine-learning algorithm to determinevarious risk profiles associated with various attributes of the userdevices 102 a-c as described above and then use the communication device107 to transmit one or more signals that indicate a determined riskprofile to user device 102 a-c. The user device 102 a-c can then protectcontent displayed on the display device 120 a-c in response to receivingthe signal even if the user device 102 a-c has not detected afield-of-view of another person or device. For example, the server 104determines that the locations of the user devices 102 a-b are associatedwith a high risk-profile. The server 104 then obtains data indicatingthe location of the user device 102 c and determines that the locationof the user device 102 c is associated with a high risk-profile inresponse to determining that the location of the user device 102 c isthe same or substantially the same as the location of the user devices102 a-b. The server 104 can then transmit a signal to the user device102 c that indicates that the location of the user device 102 c isassociated with a high risk-profile and the content protection module134 c of the user device 102 c can protect content displayed via thedisplay device 120 c even if the user device 102 c has not detected afield-of-view of another person or camera. For example, the contentprotection module 134 c obtains data indicating that confidentialcontent is being displayed via the display device 120 c and causes theprocessor 112 c to hide a portion of the confidential content inresponse to receiving the signal from the server 104 indicating that thelocation of the user device 102 c is associated with a highrisk-profile.

The user device 102 c can also determine an amount of confidentialcontent to hide based on the signal received from the server 104. Forexample, the user device 102 c receives a signal from the server 104that indicates that a location of the user device 102 c is associatedwith a high risk-profile. The user device 102 c can then hide all orsubstantially all of the confidential content based on the receivedsignal (e.g., hide all digits of a bank account number displayed on thedisplay device 120 c). As another example, the user device 102 creceives a signal from the server 104 that indicates that a location ofthe user device 102 c is associated with a low risk-profile and the userdevice 102 c hides a portion of the confidential content (e.g., lessthan all of the confidential content displayed on the display device 120c).

The user device 102 c can additionally or alternatively determine aduration of time to hide the confidential content based on the signalreceived from the server 104. As an example, the user device 102 creceives a signal from the server 104 that indicates that the locationof the user device 102 c is associated with a high risk-profile and theuser device 102 c hides all or substantially all of the confidentialcontent on the display device 120 c for a duration of time (e.g., twoseconds, five seconds, ten seconds, or any suitable duration of time) inresponse to receiving the signal. In some examples, the user device 102c hides confidential content for a longer duration of time when a signalfrom the server 104 indicates that the location of the user device 102 cis associated with a high risk-profile as compared to when a signalindicates that the location of the user device 102 c is associated witha low risk-profile.

While in this example, the server 104 obtains or receives data from theuser device 102 a-c when the user device 102 a-c determines that an eyegaze or field-of-view of a person other than a user of the user device102 a-c is directed at or toward content on the display device 120 a-cand determines various risk profiles associated with various attributesof the user device 102 a-c based on the obtained or received data, thepresent disclosure is not limited to such configurations. Rather, inother examples, the server 104 obtains or receives data from the userdevice 102 a-c when the user device 102 a-c determines that a directionof a field-of-view of another device is directed at or toward thedisplay device 120 a-c. In such examples, the server 104 determinesvarious risk profiles associated with various attributes of the userdevice 102 a-c based on the obtained or received data and transmits oneor more signals indicating a risk profile in substantially the samemanner as described above.

Moreover, in some examples, the server 104 transmits other data to theuser device 102 a-c (e.g., one or more signals other than the riskprofile or in addition to the risk profile) and the user device 102 a-ccan protect content displayed on the display device 120 a-c in responseto receiving the data even if the user device 102 a-c has not detected afield-of-view of another person or device.

In still another example, the user devices 102 a-c receives user inputindicating a particular risk profile. As an example, the user device 102c receives user input indicating a low risk-profile based on anattribute (e.g., a location) of the user device 102 c and the processor112 c of the user device 102 c can determine an amount of confidentialcontent to hide or a duration of time to hide the confidential contentbased on the received user input.

Although FIG. 1 illustrates a particular arrangement of the environment100, various additional arrangements are possible. As an example, whileFIG. 1 illustrates the user device 102 a and the machine-learningalgorithm module 108 as separate components, in some embodiments, theuser device 102 a and the machine-learning algorithm module 108 can bepart of a single system.

FIG. 2 is a flow chart depicting an example of a process 200 forprotecting content based on a detected field-of-view of a personaccording to some aspects. In some embodiments, the steps in FIG. 2 maybe implemented in program code that is executable by a processor, forexample, the processor in a general-purpose computer, a mobile device,or a server. In some embodiments, these steps may be implemented by agroup of processors. In some embodiments, one or more steps shown inFIG. 2 may be omitted or performed in a different order. Similarly, insome embodiments, additional steps not shown in FIG. 2 may also beperformed. The process 200 of FIG. 2 is described with reference toFIGS. 1 and 3, but other implementations are possible.

In block 202, content viewable by a user of a user device 102 a isdisplayed on a display device 120 a of the user device 102 a. Forexample, the user device 102 a includes a content provision module 128 athat provides the content, which can include public content orconfidential content. In some examples, the user device 102 a generatesan interface for displaying the content on the display device 120 a. Forexample, the user device 102 a generates the user interface 300 of FIG.3, which can include public content such as, for example, a currentdate. The user interface 300 can also include confidential content suchas, for example, an account number, a current account balance, and adate of a last account deposit.

In block 204, a sensor 124 a detects a field-of-view of a person otherthan the user of the user device 102 a. In some examples, the sensor 124a detects a field-of-view or a direction of an eye gaze of the otherperson relative to the display device 120 a.

In block 206, a signal about the field-of-view of the other person istransmitted to a processor 112 a of the user device 102 a. In someexamples, in block 206, a signal about the direction of the eye gaze ofthe other person can be transmitted to the processor 112 a. In someexamples, the sensor 124 a transmits the signal about the field-of-viewor the direction of the eye gaze of the other person to the processor112 a.

In block 208, a direction of an eye gaze or field-of-view of the otherperson relative to the user device 102 a is determined. For example, theuser device 102 a includes a detection module 130 a that determines thedirection of an eye gaze or field-of-view of the other person based on asensor signal received from sensor 124 a. In some examples, thedetection module 130 a determines the direction of the eye gaze orfield-of-view of the person relative to the display device 120 a of theuser device 102 a. As an example, the detection module 130 a determineswhether the other person is looking at or toward the display device 120a (e.g., looking at or toward content displayed on the display device120 a). If the other person is not looking at or toward the displaydevice 120 a, content viewable by the user of a user device 102 a cancontinue to be displayed on the display device 120 a (e.g., at block202).

If the other person is looking at or toward the display device 120 a,the process 200 further includes, in block 210, identifying confidentialcontent displayed on the user device 102 a. In some examples, the userdevice 102 a includes a content identification module 132 a that causesthe processor 112 a to identify or determine confidential or publiccontent displayed via the display device 120 a (e.g., in block 202). Forexample, the processor 112 a identifies the current date displayed inthe user interface 300 of FIG. 3 as public content and identifies theaccount number, current account balance, and the date of the lastaccount deposit displayed in the user interface 300 as confidentialcontent.

In block 212, the confidential content is protected based on thedirection of the field-of-view or the eye gaze of the other person. Forexample, the user device 102 a includes a content protection module 134a that protects content displayed via the display device 120 a. Thecontent protection module 134 a can receive or obtain data from thecontent identification module 132 a that indicates confidential contentdisplayed via the display device 120 a. As an example, the contentprotection module 134 a receives data indicating that the accountnumber, current account balance, and the date of a last account depositdisplayed in the user interface 300 of FIG. 3 is confidential content.The content protection module 134 a can also receive or obtain data fromthe detection module 130 a that indicates that an eye gaze orfield-of-view of a person other than a user of the user device 102 a isdirected at or toward content on the display device 120 a. The contentprotection module 134 a can then cause the processor 112 a to hide theconfidential content from view by the other person to protect theconfidential content (e.g., by causing the user device 102 a to generatethe user interface 302 of FIG. 3 to hide or protect the confidentialcontent).

In block 214, the content protection module 134 a determines whether theeye gaze or field-of-view of the other person is directed away from theuser device 102 a. If the other person is still looking at or toward theuser device 102 a, confidential content can continue to be protectedfrom view by the other person (e.g., at block 212). If the other personis no longer looking at or toward the user device 102 a, the process 200further includes, in block 216, revealing or unprotecting theconfidential content.

In block 216, the confidential content is revealed or unprotected basedon the direction of the field-of-view or eye gaze of the other person.For example, the content protection module 134 a determines that the eyegaze or field-of-view of the other person is no longer directed at ortoward the display device 120 a and causes the processor 112 a totransmit a signal to the display device 120 a or the content provisionmodule 128 a to unhide or reveal the confidential content for view bythe user of the user device 102 a. As an example, the content protectionmodule 134 a causes the processor 112 a to output the user interface 300of FIG. 3 that includes the public and confidential content in responseto determining that the eye gaze or field-of-view of the other person isno longer directed at or toward the display device 120 a.

FIG. 4 is a flow chart depicting another example of a process 400 forprotecting content from a field-of-view of a person or other deviceaccording to some aspects. In some embodiments, the steps in FIG. 4 maybe implemented in program code that is executable by a processor, forexample, the processor in a general-purpose computer, a mobile device,or a server. In some embodiments, these steps may be implemented by agroup of processors. In some embodiments, one or more steps shown inFIG. 4 may be omitted or performed in a different order. Similarly, insome embodiments, additional steps not shown in FIG. 4 may also beperformed. The process 400 of FIG. 4 is described with reference to theenvironment 100 of FIG. 1, but other implementations are possible.

In block 402, a server 104 obtains data indicating a first attribute ofa first user device 102 a. As an example, the user device 102 atransmits data indicating a location of the user device 102 a, a type ofthe user device 102 a (e.g., a size, shape, configuration, etc.), anapplication or program executed by a processor 112 a of the user device102 a, a type of network connection associated with the user device 102a, or any other data associated with the user device 102 a. In someexamples, the user device 102 a transmits data indicating an attributeof the user device 102 a to the server 104 in response to determiningthat an eye gaze or field-of-view of a person other than a user of theuser device 102 a is directed at or toward content on a display device120 a of the user device 102 a (e.g., in block 208 of FIG. 2).

In block 404, a risk profile associated with the first attribute of theuser device 102 a is determined. In some examples, the server 104determines the risk profile associated with the first attribute of theuser device 102 a. The server 104 can determine the risk profile bytraining a machine-learning algorithm to determine the risk profile. Insome examples, the server 104 includes a machine-learning algorithmmodule 108 that receives or obtains data from various user devices 102a-c. The machine-learning algorithm module 108 can include a riskprofile module 109 and the risk profile module 109 can train themachine-learning algorithm to determine various risk profiles associatedwith various attributes of the user device 102 a-c based on the dataobtained or received from the user device 102 a-c.

For example, the machine-learning algorithm module 108 receives dataindicating a wireless network that the user device 102 a is connected towhen the user device 102 a determines that an eye gaze or field-of-viewof a person other than a user of the user device 102 a is directed at ortoward content on the display device 120 a (e.g., in block 402). Themachine-learning algorithm module 108 can also receive data indicating awireless network that the user device 102 b is connected to when theuser device 102 b determines that an eye gaze or field-of-view of aperson other than a user of the user device 102 b is directed at ortoward content on the display device 120 b. The machine-learningalgorithm module 108 can then use the risk profile module 109 to trainthe machine-learning algorithm to determine a risk profile associatedwith the wireless network to which the user device 102 a is connected.As an example, the machine-learning algorithm module 108 uses the riskprofile module 109 to train the machine-learning algorithm to comparethe wireless networks that the user devices 102 a-b are connected to anddetermine that the wireless networks are the same or substantially thesame. The risk profile module 109 can then train the machine-learningalgorithm to determine that the wireless network that the user device102 a is connected to is associated with a high risk-profile (e.g., thatthere is a high risk that content displayed on a user device connectedto that wireless network will be viewed by a person other than the userof the user device).

In block 406, the server 104 obtains data indicating a second attributeof a second user device 102 c. For example, the server 104 obtains dataindicating a second attribute of the user device 102 c including, forexample, a location of the user device 102 c, a type of the user device102 c, an application or program executed by a processor 112 c of theuser device 102 c, a type of network connection associated with the userdevice 102 c, or any other data about the user device 102 c.

In block 408, the server 104 determines a similarity between the secondattribute of the second user device 102 c and the first attribute of thefirst user device 102 a using the machine-learning algorithm. Forexample, the machine-learning algorithm module 108 obtains dataindicating a wireless network that the user device 102 c is connected to(e.g., in block 406) and data indicating a wireless network that theuser device 102 a is connected to (e.g., in block 402). The risk profilemodule 109 then uses the machine-learning algorithm to compare thewireless networks to determine a similarity or correspondence based onthe comparison. For example, the risk profile module 109 determines thatthe wireless network that the user device 102 a is connected to is thesame or substantially the same as the wireless network to which the userdevice 102 c is connected.

In block 410, the server 104 uses the machine-learning algorithm todetermine a second risk profile associated with the second attribute ofthe user device 102 c based on the similarity between the secondattribute of the second user device 102 c and the first attribute of thefirst user device 102 a. For example, the risk profile module 109 usesthe machine-learning algorithm to determine that the user devices 102 aand 102 c are connected to the same wireless network (e.g., in block408). The risk profile module 109 can then use the machine-learningalgorithm to determine that the wireless network that the user device102 c is connected to is associated with a high risk-profile. As anotherexample, the risk profile module 109 uses the machine-learning algorithmto determine that user devices 102 a and 102 c are not connected to thesame wireless network and uses the machine-learning algorithm todetermine that the wireless network that the user device 102 c isconnected to is not associated with a high risk-profile (e.g., thenetwork is associated with a low risk-profile).

In block 412, a signal indicating the second risk profile is transmittedto the second user device 102 c. In some examples, the server 104transmits the signal to the user device 102 c. For example, as describedabove, the machine-learning algorithm module 108 uses themachine-learning algorithm to determine that the user devices 102 a and102 c are connected to the same wireless network and that the wirelessnetwork that the user device 102 c is connected to is associated with ahigh risk-profile. The server 104 can then transmit a signal to the userdevice 102 c that indicates that the wireless network that the userdevice 102 c is connected to is associated with a high risk-profile andthe content protection module 134 c of the user device 102 c can protectcontent displayed via the display device 120 c in response to receivingthe signal. In some examples, the user device 102 c determines an amountof confidential content to hide or a duration of time to hide theconfidential content based on the signal received from the server 104.

In this manner, the server 104 can obtain data from various user devices102 a-c and use the obtained data to train a machine-learning algorithmto determine various risk profiles associated with various attributes ofthe user devices 102 a-c. The server 104 can then transmit one or moresignals indicating the various risk profiles to the user devices 102 a-cand the user devices 102 a-c can protect certain content displayed onthe display devices 120 a-c from view by a person other than the user ofthe user device 102 a-c based on the received signal.

While in this example, the server 104 obtains or receives data from theuser device 102 a-c when the user device 102 a-c determines that an eyegaze or field-of-view of a person other than a user of the user device102 a-c is directed at or toward content on the display device 120 a-cand determines various risk profiles associated with various attributesof the user device 102 a-c based on the obtained or received data, thepresent disclosure is not limited to such configurations. Rather, inother examples, the server 104 obtains or receives data from the userdevice 102 a-c when the user device 102 a-c determines that a directionof a field-of-view of another device is directed at or toward thedisplay device 120 a-c. In such examples, the server 104 determinesvarious risk profiles associated with various attributes of the userdevice 102 a-c based on the obtained or received data and transmits oneor more signals indicating a risk profile in substantially the samemanner as described above. Moreover, in some examples, the server 104transmits one or more signals or any other data to the user devices 102a-c and the user devices 102 a-c can hide confidential content inresponse to receiving the signal or data.

FIG. 5 is a flow chart depicting an example of a process 500 forprotecting content based on a detected field-of-view of a deviceaccording to some aspects. In some examples, the steps in FIG. 5 may beimplemented in program code that is executable by a processor, forexample, the processor in a general-purpose computer, a mobile device,or a server. In some embodiments, these steps may be implemented by agroup of processors. In some embodiments, one or more steps shown inFIG. 5 may be omitted or performed in a different order. Similarly, insome embodiments, additional steps not shown in FIG. 5 may also beperformed. The process 500 of FIG. 5 is described with reference to theenvironment 100 of FIG. 1, but other implementations are possible.

In block 502, content viewable by a user of a user device 102 a isdisplayed on a display device 120 a of the user device 102 a. In someexamples, the content can be displayed in substantially the same manneras described above with respect to block 202 of FIG. 2.

In block 504, a sensor 124 a detects a presence, location, orfield-of-view of a device other than the user device 102 a. The devicecan be any device that may include a camera, sensor, or other componentthat can capture or view content on the display device 120 a of the userdevice 102 a. For example, the device can include a mobile device, asmartphone, a laptop, tablet, e-reader, smartwatch, etc.

In some examples, the sensor 124 a can detect a presence, location,proximity, or field-of-view of the other device relative to the userdevice 102 a or the display device 120 a via any suitable technique ormethod. As an example, the sensor 124 a can include a Bluetooth deviceor other network device that can detect a presence, location, orproximity of another Bluetooth device or another network device byanalyzing the strength of a signal between the sensor 124 a and theother Bluetooth device or network device. As another example, the sensor124 a can capture an image of the other device and the captured imagecan be used to determine a presence, location, proximity, orfield-of-view of the other device relative to the user device 102 a orthe display device 120 a.

In block 506, a signal about the presence, location, or field-of-view ofthe other device is transmitted to a processor 112 a. In some examples,the sensor 124 a transmits the signal about the presence, location, orfield-of-view of the device to the processor 112 a.

In block 508, the location or a direction of a field-of-view of theother device relative to the user device 102 a is determined. Forexample, the user device 102 a includes a detection module 130 a thatcauses the processor 112 a to determine the presence, location,proximity, or field-of-view of the other device. In some examples, thedetection module 130 a causes the processor 112 a to determine thepresence, location, proximity, or field-of-view of the other devicebased on a sensor signal received from the sensor 124 a (e.g., a sensorsignal transmitted in block 506).

For example, the sensor 124 a is a Bluetooth device or other networkdevice that can detect a location of another Bluetooth device and thedetection module 130 a can cause the processor 112 a to determine alocation of the other Bluetooth device or proximity of the otherBluetooth device by analyzing the strength of a signal between thesensor 124 a and the other Bluetooth device. As another example, thesensor 124 a captures an image of the other device and then transmits asignal indicating the captured image to the processor 112 a and theprocessor 112 a determines the direction of the field-of-view of acamera or sensor of the other device relative to content on the displaydevice 120 a based on the image by using various image processingmethods and techniques. For example, the processor 112 a determineswhether the direction of the field-of-view of the camera or sensor ofthe other device is directed at or toward the display device 120 a. Ifthe other device is not near the user device 102 a or if the camera orsensor of the other device is not directed at or toward the displaydevice 120 a, content viewable by the user of a user device 102 a cancontinue to be displayed on the display device 120 a (e.g., at block502).

If the other device is near the user device 102 a or if the camera orsensor of the other device is directed at or toward the display device120 a, the process 500 further includes, in block 510, identifyingconfidential content displayed on the user device 102 a. In someexamples, a content identification module 132 a can identify theconfidential content in substantially the same manner as described abovewith respect to block 210 of FIG. 2.

In block 512, the confidential content is protected based on thelocation or the direction of the field-of-view of the other device. Forexample, the user device 102 a includes a content protection module 134a that protects content displayed via the display device 120 a. Thecontent protection module 134 a can obtain or receive data from thecontent identification module that indicates confidential contentdisplayed via the display device 120 a. The content protection module134 a can also receive or obtain data from the detection module 130 athat indicates that a direction of a field-of-view of the other deviceis directed at or toward the display device 120 a. The contentprotection module 134 a can then cause the processor 112 a to hideconfidential content from view by the other device to protect theconfidential content. In some examples, the content protection module134 a receives or obtains data indicating that a location or proximityof the other device is near the location of the user device 102 a andthe content protection module 134 a causes the processor 112 a to hideconfidential content from view by the other device.

In block 514, the content protection module 134 a determines if theother device is located away from the user device 102 a or if the cameraor sensor of the other device is directed away from the user device 102a. If the other device is still located near the user device 102 a or ifthe camera or sensor of the other device is still directed toward theuser device 102 a, confidential content can continue to be protectedfrom view by the other device (e.g., at block 512). If the other deviceis located away from the user device 102 a or if the direction of thefield of view of the camera or sensor of the other device is no longerdirected at or toward the user device 102 a, the process 500 furtherincludes, in block 516, revealing or unprotecting the confidentialcontent.

In block 516, the confidential content is revealed or unprotected basedon the location or direction of field-of-view of the other device. Forexample, the content protection module 134 a determines that thedirection of the field-of-view of the other device is no longer directedat or toward the display device 120 a and causes the processor 112 a totransmit a signal to the content provision module 128 a or the displaydevice 120 a to unhide or reveal the confidential content for view bythe user of the user device 102 a. In some examples, the contentprotection module 134 a can reveal or unprotect the confidential contentbased on the location or the direction of the field-of-view of the otherdevice in substantially the same manner as described above with respectto block 216 of FIG. 2.

The foregoing description of certain examples, including illustratedexamples, has been presented only for the purpose of illustration anddescription and is not intended to be exhaustive or to limit thedisclosure to the precise forms disclosed. Numerous modifications,adaptations, and uses thereof will be apparent to those skilled in theart without departing from the scope of the disclosure.

What is claimed is:
 1. A computing device comprising: a display device; a processing device; and a non-transitory computer-readable medium communicatively coupled to the processing device, the non-transitory computer-readable medium comprising instructions that are executable by the processing device for: receiving a risk profile indicative of a likelihood of content on the display device being accessed by at least one of a third-party device or a person other than a user of the computing device, the risk profile associated with at least one of a particular location, a particular application or program, a particular type of computing device, or a particular type of network; determining a field of view of the display device; identifying confidential content in the computing device for display on the display device; and protecting, based on the risk profile and in response to determining the field of view, the confidential content.
 2. The computing device of claim 1, wherein the instructions are further executable by the processing device for determining a direction of view of the third-party device or the person other than the user of the computing device, and wherein the protecting of the confidential content is further in response to determining the direction of view.
 3. The computing device of claim 2, wherein the instructions are further executable by the processing device for determining an eye gaze the person other than the user of the computing device and the direction of view is determined at least in part based on the eye gaze.
 4. The computing device of claim 1, wherein the instructions are further executable by the processing device for displaying public content on the display device while hiding or blurring the confidential content on the display device.
 5. The computing device of claim 4, wherein the instructions are further executable by the processing device for determining at least one of an amount of the confidential content to hide or blur, or a duration of time to hide or blur the confidential content.
 6. The computing device of claim 1, wherein the instructions are further executable by the processing device for transmitting an attribute of the computing device, wherein the risk profile corresponds at least in part to the attribute of the computing device.
 7. The computing device of claim 1, wherein the instructions are further executable by the processing device for detecting the third-party device within the field of view of the display device by analyzing a strength of a signal from the third-party device.
 8. A non-transitory computer-readable medium that includes instructions that are executable by a computing device for causing the computing device to perform operations for protecting confidential content, the operations comprising: receiving a risk profile indicative of a likelihood of content displayed by the computing device being accessed by at least one of a third-party device or a person other than a user of the computing device, the risk profile associated with at least one of a particular location, a particular application or program, a particular type of computing device, or a particular type of network; determining a field of view of the computing device; identifying confidential content in the computing device for display on the computing device; and protecting, based on the risk profile and in response to determining the field of view, the confidential content.
 9. The non-transitory computer-readable medium of claim 8, wherein the operations further comprise determining a direction of view of the third-party device or the person other than the user of the computing device, and wherein protecting the confidential content is further in response to determining the direction of view.
 10. The non-transitory computer-readable medium of claim 9, wherein the operations further comprise determining an eye gaze the person other than the user of the computing device and the direction of view is determined at least in part based on the eye gaze.
 11. The non-transitory computer-readable medium of claim 8, wherein the operations further comprise displaying public content on the computing device while hiding or blurring the confidential content on the computing device.
 12. The non-transitory computer-readable medium of claim 11, wherein the operations further comprise determining at least one of an amount of the confidential content to hide or blur, or a duration of time to hide or blur the confidential content.
 13. The non-transitory computer-readable medium of claim 8, wherein the operations further comprise transmitting an attribute of the computing device, wherein the risk profile corresponds at least in part to the attribute of the computing device.
 14. The non-transitory computer-readable medium of claim 8, wherein the operations further comprise detecting the third-party device within the field of view of the computing device by analyzing a strength of a signal from the third-party device.
 15. A method comprising: receiving, by a processing device, a risk profile indicative of a likelihood of content displayed by a computing device being accessed by at least one of a third-party device or a person other than a user of the computing device, the risk profile associated with at least one of a particular location, a particular application or program, a particular type of computing device, or a particular type of network; determining, by the processing device, a field of view of the computing device; identifying, by the processing device, confidential content in the computing device for display on the computing device; and protecting, by the processing device, based on the risk profile and in response to determining the field of view, the confidential content.
 16. The method of claim 15 comprising determining a direction of view of the third-party device or the person other than the user of the computing device, and wherein protecting the confidential content is further in response to determining the direction of view.
 17. The method of claim 15 comprising displaying public content on the computing device while hiding or blurring the confidential content on the computing device.
 18. The method of claim 17 comprising determining at least one of an amount of the confidential content to hide or blur, or a duration of time to hide or blur the confidential content.
 19. The method of claim 15 comprising transmitting an attribute of the computing device, wherein the risk profile corresponds at least in part to the attribute of the computing.
 20. The method of claim 15 comprising detecting the third-party device within the field of view of the computing device by analyzing a strength of a signal from the third-party device. 